A. Field of the Invention
This invention relates to agricultural and, in particular, to automatic identification of seed-specific information about agricultural seeds, including prior to planting, during planting, and after planting.
B. Problems in the Art
Precision agriculture continues to advance. Likewise does utilization of more and more data regarding the entire process. More information about each stage of agricultural production can be beneficial to a variety of stakeholders, including the farmer/producer. However, like any data collection and processing system, accuracy is critical. One example is being able to identify seed or plant variety or hybrid accurately and efficiently.
Advances in plant science, including plant breeding and genetic modification, has led to an explosion of different varieties or hybrids to meet different producer goals or environmental conditions. The ability to accurately know and monitor specific seed or plant hybrid or variety is important to not only knowing what is going to be planted, but also what is planted in the ground. Furthermore it is important to making future decisions about the next growing season or seasons. However, as will be demonstrated below, keeping track of seed- or plant-specific information, even for sets of seed or plants, is not a trivial endeavor.
For example, seed customers (e.g. farmers/producers) often forget when they add more seed to a planter that it may be a different hybrid than originally planted and, therefore, they can forget to change the identification of the hybrid in, for example, a precision agriculture system they are using. This causes the farmers to log incorrect data and make poor management decisions because of the incorrect hybrid being logged. For example, the producer might choose variety X for next year's planting season because it was believed to have yielded better, but it was really variety Y that was planted.
Furthermore, even if the farmer remembers to change the hybrid logging at seed switch-over during planting, there is always the risk of human error in the entry of that information into the system. Such potential errors can occur at other points in the agricultural production cycle. Seed company representatives rely on the farmer to tell them what hybrid was planted in which fields. If such a trusted advisor is told it is seed X when it really is not, this can cause confusion, unnecessary work, and poor management decisions.
Another example is the step of recording of hybrid or variety type, or other information about seed or a crop from the seed. Such tracking and documentation can take many forms. It can range from keeping the labels off of seed bags or other packaging, to handwriting information into a notebook, to manual entry into the computerized precision farming system. In all these cases risk of human error exists.
A still further example is user overhead. Although a subtle burden, manual entry of seed-specific data at even one point or stage of agricultural production (e.g. when re-loading a planter) takes valuable time. Cumulatively, over all planting for a season, it can add up and impact productivity.
Therefore, there is a need for improvement in being able to automatically identify seed or plant variety or hybrid type, and/or other seed-specific information, that is accurate, efficient, immediate, and practical, not only at the planting stage but at other stages of production.
There are known ways to identify plant-specific information. Many tend to be high technology ways to identify plant genotype. Some examples are destructive in the sense they remove seed or plant tissue and investigate it in a laboratory setting. This might be reasonable for some limited research settings or for seed production companies, but not for farmers. Sophisticated techniques such as aerial-based spectrometry can be used to try to identify plant genotype for plants growing in the field. But it is difficult to have resolution down to row-by-row or plant-by-plant with such techniques. They are complex, costly, and can only work for growing plants and not seed.
There have been attempts to use Automated Identification and Data Capture (AIDC) to allow machine-readable data to be associated with seeds or plants. One example is bar codes. However, they require unobstructed line-of-sight for the reader and maintenance of the UPC graphics. It is sometimes difficult to accurately read bar codes when the bar code or the reader is moving. All this makes it difficult to use bar codes with seeds or agricultural production. In particular, it represents limitations on the degree to which a bar code can follow and be correlated to other than seed packages, as opposed to seed throughout the production process from packaging, to planting, to harvest.
The assignee of the present application has invented and patented a technique of tracking harvested crops, including grain crops like corn and soybeans. See U.S. Pat. No. 8,810,406 to inventor Sell and owned by Ag Leader Technology, In., Ames, Iowa (USA), which is incorporated by reference herein. Objects with RFID tags are added to the harvested grain flow. The RFID tags are both readable and writeable to add specific information about the grain as it is harvested. Traceability of such grain is made possible by using RFID scanners or readers to interrogate the grain with the inserted RFID tagged objects, or a portion of it. This can be on-board the harvester, in a wagon or hopper to transport the grain, or at a storage facility. The user makes the assumption that harvested grain in close proximity to the objects with RFID tags correlate to the grain specific data written in the RFID tag. The objects with the RFID tags can be manufactured to simulate the form factor and other characteristics of the actual grain being harvested so that they tend to stay dispersed and react to post-harvest processing in a similar manner to the actual grain. See also, U.S. Pat. No. 7,162,328 to inventors Hornbaker et al. and assigned to the University of Illinois, also incorporated by reference herein. It also relates to tracking grain after harvest using RFID tagged objects mixed into the harvested grain. In both these patents, a bulk quantity of RFID tagged objects has to be carried on-board a harvester and then metered into a bulk quantity of actual harvested grain. Also, the systems require components to automatically remove or filter out the RFID tagged objects at some point from the actual grain.
Providing seed-specific data for seed to be planted presents a different set of issues. Some of them are antagonistic to each other. For example, seed for planting is usually produced by an entity other than the farmer. It is typically bagged or packaged prior to delivery. There can be significantly different information about seed, not only its variety or hybrid but usage restrictions. It must be removed from packaging and go through quite precise handling at the planter. And it must then be placed in the ground, outside of any packaging, implements, or containers so that it can grow. These factors present a different set of competing factors to keep correlation of actual seed to readable data about such seed than handling of bulk harvested grain. Introduction of foreign or non-seed into the process is contra-indicated.
Therefore, the inventor has identified room for improvement in this technological area.